This disclosure presents various embodiments of a method of segmenting an image into halftone and non-halftone regions. In several embodiments, the method is applied to define a process for identifying a block of pixels in a grayscale image to define a binary image, identifying a group of connected pixels in the binary image to define a region of interest, and to process the region of interest for classification as a halftone or non-halftone region based at least in part on using a scale invariant feature transform (SIFT) algorithm. However, the method can also be applied to multiple groups of connected pixels from the same block and to multiple blocks of pixels from the grayscale image. Parallel processing can be used to process multiple groups of connected pixels. Similarly, parallel processing can be used to process multiple blocks of pixels. Various embodiments of an image processing device for performing the method are also provided. The disclosure also presents various embodiments of a computer-readable medium storing program instructions that, when executed, cause an image processing device to perform the method.
For copy and scan jobs, different regions in the original image, such as contone, halftone, text and lines are usually processed differently for rescreening or for compression respectively. Separation of text regions from the rest of the objects is the main challenge in segmentation of the original image.
Separation of halftone and non-halftone regions in a document image is vital for numerous purposes, such as: i) to avoid image quality artifacts when rescreening the image while copying, ii) for better text recognition using OCR on scanned documents, iii) to improve any type of information extraction, such as data in forms, etc., and iv) for better image compression performance.
The existing approaches to separation of halftone and non-halftone regions have various limitations, such as: i) auto-windowing based methods are computationally complex for real time/software implementation in MFDs, as pixel based micro-segmentation tags are generated using algorithms implemented in ASICs; ii) in connected component based approaches, selecting proper threshold to form the connected component is difficult and, if the proper threshold is not selected, the possibility of misclassification is higher, iii) since the raw image handled by MFD's is of high resolution, time and computation costs are higher, and iv) when there is scale or rotational variation in the image, usage of certain methods (e.g., run-length) fails in determining halftone regions.